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For International Customer E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction How to Create EQS Actions Add Queue under tab Actions for queue service Using SDK Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS How to Create Functions Functions Information Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group How to create Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registry Simplifying Pull Operations with UserFriendly Interface API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation SignUp Process and Myaccount Dashboard Access For International Customer For International Customer SignUp with Foreign Customer as Organization Navigate to URL httpsmyaccounte2enetworkscomaccountslogin Click on Not registered Sign up link then SignUp page will be open Fill all details and Click on SignUp button After Fill all details and Click on SignUp button OTP verification pop up would be open You have to fill out an OTP which has been sent on your mobile number and your Email and click on the Verify button After OTP verification the Billing information page will be open User needs to fill the required field Note We dont ask for GSTIN and PAN in case of Foreign customers We only ask for VATTAX ID in case of Organization and that field is not mandatory as of now After filling in all details and after clicking on Next button the customer validation process will be start Skip Validation If the user will click on skip button then another pop will appear on the customer has to click on Skip validation Note After skip verification user will be able to use myaccount but only for 20 days and a warning message will be displayed on their myaccount dashboard the warning message will be like this Your customer validation process is pending Please complete validation before the datelike 2023036 to use uninterrupted services Click here to complete your customer validation If the user will not complete their customer validation within 20 days then we will suspend his account after 20 days For suspending we will send a first reminder on the 4th day after SignUp and a second reminder we will send on the 7th day after registration and then 3rd or final reminder will be on the 9th day But still the customer will not complete his validation after 10 days his account will be suspended Now after a few days of using services customer wants to validate his account then he will have to click on the Click here link After clicking on the link a popup will appear and shows a message like stripe based validation for the services for E2E networks ltd Here customer choose complete on mobile verification or Continue on this device when customer choose mobile verification click on complete on mobile verification After clicking complete on mobile verification button then show multiple option like using QR Code SMS email and using link option Using QR Code Using SMS Using Email Using Link when customer choose Continue on this device Provide Photo ID On this page SignUp with Foreign Customer as Organization Skip Validation Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited |
E2E User Management Documentation E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction How to Create EQS Actions Add Queue under tab Actions for queue service Using SDK Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS How to Create Functions Functions Information Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group How to create Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registry Simplifying Pull Operations with UserFriendly Interface API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation Other Services on E2E Networks E2E User Management Documentation E2E User Management Documentation Get started Introduction IAM Identity and Access Management Create Manage Contacts Add New Contacts Manage Contacts Delete Contacts Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited |
Natural Language Queries to SQL with CodeLlama E2E Networks documentation Skip to content E2E Cloud Docs E2E Networks TIR Toggle navigation menu Login Sign Up E2E Networks documentation K Docs E2E Networks TIR Myaccount Getting Started with Myaccount SignUp Process for Indian Customers Customer validation Process for Indian Customers SignUp Process for International Customers Customer Validation Process for International Process Customer Validation Process for Contact Persons Domestic Customer Validation Process FAQs International Customer Validation Process FAQs Sign In Process Release Notes Compute Nodes Virtual Compute Nodes Monitoring 1Click Deployment Active Directory GPU GPU Cloud EQS Introduction Appliance Load Balancer Appliance Auto Scaling Introduction Concepts Define Scale Groups FaaS Function as a Service FaaS Network CDN VPC How to reserve an IP address Reserve IP Pool DNS Custom Reverse DNS Firewall Security Group Tag Security Firewall Bitninja Best Practices SSH Key Management Audit Logs Password Policy 2Factor Authentication Others License Management User Management Purchase SSL CertbotPlugin Apply or Redeem Coupon Code Account Statement Cloud Platform Support Introduction Platform Support Policy FAQ E2Es MyAccount FAQs Code of Conduct of Directors and Senior Management CSR Policy Whistle blower policy Jitsi Meet Mod Evasive Multisite using cPanel Softaculous Copying data from Linux to Windows using WinSCP Migrate MySQL Database Between DBaaS Manage MySQL Abuse Abuse Logs Abuse Attacks Spam Mails Phishing Complaint Copyright Complaint Billing Payment Payment Method EMandate Redeem Coupon Customer Details Updation Setup AutoDebit feature TDS Deduction process Declaration us 206AB Minimum Billing Provisioning and Deprovisioning Process View Invoice and Payment Prepaid Billing Set up Infra Credits Balance Alert Whatsapp notification for Payment reminder Restore Service on a Suspended Account for NonPayment Database Database Database PostgreSQL Parameter Group MongoDB mariaDB Storage Storage Block Storage Object Storage CDP Backup Scalable File System Kubernetes Kubernetes Service Kubernetes Kubernetes Marketplace Monitoring Stack Cert Manager Nginx Ingress Controller Troubleshooting Argo CD Declarative GitOps CD for Kubernetes Deploy to Kubernetes using Argo CD and GitOps Jenkins CI Tool Setup Jenkins On Kubernetes Cluster Ansible CD Tool Istio Service Connecting to Dbaas FAQS Container Registery Container Registery API Developers Guide API SDK E2E CLI Tool Introduction Terraform Terraform Getting Started e2enode Resource Node Plans e2eimage Resource AIML TIR AI Release Notes TIR AI Platform Introduction Getting Started Howto Guides Projects Notebooks Committed Notebook GPU H100 Plans Datasets Model Repository Model Endpoints Pipeline Run Scheduled Run Fine Tuning Models Model Playground Samples and Tutorials API Tokens SSH Key Container Team Features Settings Analytics Billing AIML Tutorials Finetune LLMA with Multiple GPUs Deploy Inference for LLMA 2 Deploy Inference for Codellama Deploy Inference for Stable Diffusion v21 Finetune Stable Diffusion model on TIR Deploy Inference for MPT7BCHAT Custom Containers in TIR Fine Tuning Bloom Natural Language Queries to SQL wth Code Llama E2E Networks documentation Welcome to TIR AI Platform Documentation Tutorials Natural Language Queries to SQL with CodeLlama Natural Language Queries to SQL with CodeLlama Introduction Utilizing natural language queries for SQL database interaction represents a revolutionary paradigm shift streamlining the complexities of database management and querying This innovative approach harnesses the power of natural language processing NLP techniques enabling users to engage with relational databases using everyday language free from the constraints of intricate SQL coding It empowers users to pose inquiries or request data from databases in a conversational manner mirroring human interactions By bridging the chasm between human language and SQL this technology democratizes database accessibility simplifying data extraction and comprehension for nontechnical users grappling with extensive datasets Natural Language Queries NLQ offer a transformative boost to data accessibility and usability expediting decisionmaking processes across diverse domains encompassing realms from business intelligence to data analysis and reporting This approach proves particularly advantageous for data administrators affording them the capability to pose inquiries naturally circumventing the need for direct code composition Technologies CodeLlama developed by Meta AI is a sophisticated large language model LLM chatbot This AI model is extensively trained on a vast corpus of text and code granting it the capability to perform a variety of tasks including text generation language translation creative content creation and providing informative responses to questions One of its standout features is its ability to convert natural language queries into SQL queries CodeLlama is a specialized version of the Llama2 language tool finetuned specifically for tasks involving coderelated content It has been meticulously trained on codecentric datasets to offer a deeper and more specialized understanding yielding precise outputs in the realm of codespecific domains CodeLlama is available in three parameter sizes 7B 13B and 34B catering to different use cases Additionally it boasts a unique Fill in the Middle FIM feature enabling it to seamlessly insert code snippets into existing code structures Furthermore there are two distinct finetuned iterations of CodeLlama The first CodeLlama Python has undergone additional training on a substantial dataset of 100 billion tokens of Python code enhancing its proficiency in Pythonrelated tasks The second CodeLlama Instruct excels in understanding and interpreting natural language queries effectively discerning user expectations and providing relevant responses to prompts LLama 2 architecture used for Code llama The texttoSQL task is a complex challenge that revolves around automatically translating natural language text into SQL queries This challenge is particularly daunting due to the inherent ambiguity in natural language queries as they can encompass various entities and relationships within a database CodeLlama plays a pivotal role in addressing this task by first comprehending the underlying meaning of the given natural language query and subsequently crafting the corresponding SQL query The process employed by CodeLlama initiates with a natural language parser which dissects the natural language query into its fundamental components This parsing phase discerns the entities relationships and required operations specified within the query Subsequently CodeLlama harnesses this comprehensive representation to generate a semantically accurate SQL query tailored for execution within a database environment CodeLlama has demonstrated remarkable effectiveness in the realm of translating natural language queries into SQL In a recent research endeavor CodeLlama exhibited an impressive capability to produce correct SQL queries for 85 of the queries contained within a standard benchmark dataset This achievement signifies a substantial advancement compared to previous methodologies for tackling the texttoSQL challenge Prerequisites To test it out first you need to head to E2E Cloudhttpsmyaccounte2enetworkscom and sign in or sign up for an account Once in click on TIR AI Platform on top to switch to the AI Platform You can now create a notebook Free tier is available and that suffices for the following experiment Create Notebook on TIR Once thats done you can Launch the Notebook and move on to the next step How to Use and Querying Examples Meta has released their code on their github repository for Codellama One can also download the model by sending a request to MetaAI for the model access httpsaimetacomresourcesmodelsandlibrariesllamadownloads However instead of going through the hassle of doing so one can also directly use the CodeLlama model inference API through HuggingFace httpshuggingfacecocodellamaCodeLlama34bInstructhf To use the model API here is a simple code that can be run directly on TIR on E2E Cloud pip install transformers pip install accelerate This piece of code downloads the required libraries to TIR notebook from IPythondisplay import Markdown display This import is important for displaying the output in a more readable manner import requests inputFind the names of all employees who are from California APIURL httpsapiinferencehuggingfacecomodelscodellamaCodeLlama34bInstructhf headers Authorization Bearer hfXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX def querypayload response requestspostAPIURL headersheaders jsonpayload return responsejson output query inputs input whileoutput0generatedtextinput inputoutput0generatedtext outputqueryinputsinput This is a piece of code for direct inference from the CodeLlama Inference 34B parameters model The input shown here is just an example input and it can be changed depending on the prompt the user wants It should also be noted here that the Authorization API key is unique to each person and can be generated directly through HuggingFace httpshuggingfacecosettingstokens It should also be noted that the output here is being generated multiple times to ensure that the SQL query generated is complete therefore it is run until the inference API does not generate any new output from the input displayMarkdownoutput0generatedtext This final cell is for reading the final output The output can be found below Example queries and their outputs from CodeLlama Inference 34B parameters Query Retrieve the names and email addresses of all customers who made a purchase in the last month and spent more than 100 Output SELECT name email FROM customers WHERE id IN SELECT customerid FROM orders WHERE totalamount 100 AND createdat DATESUBNOW INTERVAL 1 MONTH Query Find the average salary of employees in each department along with the total number of employees in each department for departments with more than 10 employees Additionally display the department name and the highest salary within each of those departments Output SELECT dname AS departmentname AVGesalary AS averagesalary COUNTeidAS totalemployees MAXesalary AS highestsalary FROM departments d JOIN employees e ON did edepartmentid GROUP BY dname HAVING COUNTeid 10 It should be ensured that the prompts that are entered should not be ambiguous and should contain the entire information required by the model to generate a valid SQL query which will work well An example of such prompt and its output is given below Query Retrieve the names and email addresses of all employees in the Sales department who joined the company after January 1 2022 sorted by their hire date in ascending order Output SELECT firstname lastname email FROM employees WHERE departmentid SELECT id FROM departments WHERE name Sales AND hiredate 20220101 ORDER BY hiredate ASC Challenges and Solutions Variability in SQL Dialects Challenge SQL dialects vary depending on the database system MySQL Oracle PostgreSQL making it essential to generate compatible SQL queries Solution Tailor queries to the specific SQL database system in the appropriate dialect Handling Complex Queries Challenge Complex SQL queries involving multiple joins subqueries and aggregations can be difficult to generate accurately from natural language input Solution Implement a robust query generation engine capable of handling a wide range of SQL constructs Incorporate algorithms that deconstruct complex queries into simpler subqueries and reassemble them Lack of Data Context Challenge Natural language queries often lack contextual information crucial for accurate query generation eg understanding Show me the sales for this year Solution Enhance contextawareness by considering the users session history or explicitly incorporating contextual information into the query Handling Large and Complex Databases Challenge Mapping natural language queries to the appropriate schema can be challenging in databases with numerous tables and columns Solution Implement a robust schema mapping mechanism utilizing database metadata to aid query generation Encourage user feedback to refine mapping accuracy Error Handling and User Feedback Challenge Effective error handling and user feedback mechanisms are essential when CodeLlama generates incorrect SQL queries Solution Develop a userfriendly interface that explains errors and provides correction suggestions Leverage user feedback to continually enhance query accuracy Security and Data Privacy Challenge Ensuring security and data privacy when granting natural language access to databases is critical Solution Implement strong access control and authentication mechanisms Restrict query execution to prevent unauthorized access to sensitive data User Acceptance and Learning Curve Challenge Users may initially struggle to adapt to querying databases using natural language Solution Offer user training and comprehensive documentation to help users become proficient with the system Introduce the technology gradually to ease the transition Addressing these challenges during the development and deployment of a TexttoSQL system like CodeLlama is paramount to ensure accuracy usability and security in realworld applications Continual improvement driven by user feedback and advancements in NLP and AI technologies will further enhance the efficacy of such systems Conclusion CodeLlama stands out as an exceptional tool for transforming natural language queries into precise SQL statements outperforming even stateoftheart models particularly in codespecific and texttoSQL applicationsa primary focus of this article Its ease of use is a testament to its usability offering a seamless experience for SQL query generation However its crucial to underscore that the effectiveness of CodeLlama hinges on the specificity and precision of the provided natural language queries To maximize its utility users should ensure their queries leave no room for ambiguity or assumptions The tool thrives when users articulate their questions with meticulous clarity In the real world TexttoSQL models like CodeLlama find applications across diverse scenarios greatly benefiting data administrators and professionals in various fields These tools empower users to interact with databases more intuitively and efficiently Nonetheless its imperative to recognize that CodeLlama while a powerful asset should not be viewed as a standalone solution Rather it should be regarded as a valuable tool that enhances human capabilities and simplifies complex tasks When used in conjunction with domain expertise and best practices CodeLlama can significantly streamline datarelated workflows and amplify productivity On this page Introduction Technologies LLama 2 architecture used for Code llama Prerequisites How to Use and Querying Examples Challenges and Solutions Conclusion Products TIR AI Platform GPU Dedicated Compute CPU Intensive Cloud High Memory Cloud Linux Smart Dedicated cPanel Linux Cloud Windows Cloud Windows SQL Cloud Plesk Windows Cloud GPU Smart Dedicated Load Balancer Company About Us Meet the Team Become a Partner E2E in Media Testimonials Investors Careers Contact Us Contact Sales Escalation Matrix Service Level Agreement Terms of Service Privacy Policy Refund Policy Policy FAQ Resources Blog Events Service Health Status Help White Papers Ecosystem Enablers Customers Certifications Countries Served FAQs E2E Networks Limited E2E Networks Limited is a NSE Listed AIFirst Hyperscale Cloud Computing Platform CIN Number L72900DL2009PLC341980 Copyright 2023 E2E Networks Limited |